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1998 American control Conference, ACC 1998

作者： Docter, William A. Georgakis, Christos Chemical Process Modeling and Control Research Center Department of Chemical Engineering Lehigh University 111 Research Drive Bethlehem PA 18015 United States

ISBN: (纸本)0780345304

This paper presents a general methodology for developing Nonlinear Low Order Model (NLLOM) from data collected from large detailed nonlinear models. This methodology is divided into two tasks: development of an Average Linear Low Order Model (ALLOM) and augmentation of the ALLOM with selected nonlinear terms to form the NLLOM. The tools required for the augmentation step that is the focus of this paper include stepwise regression and nonlinear optimization. Results will be presented for the application of these techniques in the development of an NLLOM from a detailed high purity air separation distillation column model supplied by Praxair, Inc. © 1998 AACC.

关键词： Nonlinear programming

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Static anti-windup controller synthesis using simultaneous convex design

Static anti-windup controller synthesis using simultaneous c...

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05AIChE: 2005 AIChE Annual Meeting and Fall Showcase

作者： Tiwari, Pradeep Y. Mulder, Eric F. Kotharel, Mayuresh V. Chemical Process Modeling and Control Center Department of Chemical Engineering Lehigh University Bethlehem PA 18015 United States ExxonMobil Chemical 5000 Bayway Drive Baytown TX 77520

We present a method for the synthesis of a control law which incorporates both a traditional linear output-feedback controller as well as a static anti-windup compensator. Unlike traditional anti-windup controller design in which the linear controller and anti-windup compensator are designed sequentially, our method synthesizes all controller parameters simultaneously, thus providing a priori account of the effects of saturation on the closed-loop dynamics. Moreover, we derive sufficient conditions for the quadratic stability and (possibly) multiple performance bounds on the closed-loop dynamics such that the entire synthesis is cast as an optimization problem over linear matrix inequalitics (LMIs).

关键词： Feedback control

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State estimation and control of spray etching processes

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Journal of process control 1992年第2期2卷 87-101页

作者： Kao, Alan S. Stenger, Harvey G. Georgakis, Christos Covert, Kathleen L. Chemical Process Modeling and Control Center Lehigh University Bethlehem PA 18015 Iacocca Hall United States The IBM Corporation Endicott NY 13760 1701 North Street United States

Several Kalman filter designs were developed and tested for controlling a spray etching process. A hybrid extended Kalman filter was found to yield biased estimates in the presence of process-model mismatch. This issue was resolved by augmenting the state vector with poorly known parameters and developing a proportional-integral Kalman filter. These parameters are treated as stochastic processes, through which the estimate bias of the extended Kalman filter is eliminated. The resulting filter designs are capable of providing accurate estimates of the etching species concentrations as well as making available frequent estimates of the etch profile characteristics, which are only measured at infrequent intervals. © 1992.

关键词： Kalman filters spray etching state estimation

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Nonlinear Term Selection and Parameter Estimation in the Identification of Nonlinear Reduced Order State Space Models

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IFAC Proceedings Volumes 1998年第11期31卷 335-340页

作者： William Docter Christos Georgakis Chemical Process Modeling and Control Research Center and Department of Chemical Engineering Lehigh University Bethlehem Pennsylvania USA

This paper presents a general methodology for the development of Nonlinear Low Order Models (NLLOM) from data collected from detailed nonlinear simulation models. This methodology is divided into two tasks: development of a Average Linear Low Order Model (ALLOM) and augmentation of the ALLOM to form a NLLOM, the latter task being the focus of this paper. The tools examined for the nonlinear augmentation of the ALLOM include stepwise regression and nonlinear optimization. Results will be presented for the application of these techniques towards the development of an NLLOM from a detailed high purity distillation simulation.

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A New Measure of process Output controllability

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IFAC Proceedings Volumes 1998年第11期31卷 663-672页

作者： David R. Vinson Christos Georgakis Chemical Process Modeling and Control Research Center and Department of Chemical Engineering Lehigh University Bethlehem PA 18015

A steady state, multivariable, and nonlinear measure is presented for assessing the input-output, open-loop controllability of a process. This measure is ascertaining the inherent controllability of the process, as it is calculated in the absence of any regulatory control structure. It is also independent of the inventory control structure that might be assumed present in order to keep the inventory levels constant. This measure evaluates the ability of a design to reach all points of the desired output space and to reject the expected disturbances utilizing input action not exceeding the available input space. Besides being applicable to a SISO case, its multivariable character is shown to be more accurate than existing measures such as RGA, minimum singular value, and condition number.

关键词： control theory controllability Distillation columns Inputs Nonlinear gain Output Polygons

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Steady State Optimal Test Signal Design for Constrained Multivariable Systems

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IFAC Proceedings Volumes 2000年第15期33卷 1213-1218页

作者： Qiang Zhan Christos Georgakis Chemical Process Modeling and Control Center and Dept. of Chemical Engineering Lehigh University Bethlehem PA 18015

A new input signal design method is proposed for constrained multivariable systems that aims to maximize the signal to noise ratio while also meeting certain input and output constraints. The proposed methodology utilizes an approximate steady state model that is assumed to be known a-priori. The steady state operability concepts are used to incorporate the steady state input and output constraints into the signal design. The input test signal design problem is formulated as a nonlinear optimization problem and it is shown that all the existing methods can be unified under this proposed design framework. It will be proven that the design method is D-optimal from a steady state perspective. For ill-conditioned systems, more energy will be automatically directed in the weak directions. An example will be given to demonstrate the superiority of the method.

关键词： Identification Input Signal Design Multivariable control

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Wavelet techniques in the compression of process data

Wavelet techniques in the compression of process data

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American control Conference (ACC)

作者： M.J. Watson A. Liakopoulos D. Brzakovic C. Georgakis Chemical Process Modeling and Control Research Center Lehigh University USA Chemical Process Modeling and Control Research Center Lehigh University Bethlehem PA USA

The objective of this paper is to explore the application of wavelets to the field of data compression in the process industry. The wavelet transform is compared with the discrete Fourier and cosine transforms. To examine a complete approach to data compression, quantization techniques are applied to the transformed coefficients. Different quantiser designs are used for the compression of data from an industrial distillation column. Comparisons are made with the Box-Car and backward-slope methods currently used in the process industries.

关键词： Data compression Discrete wavelet transforms Quantization chemical processes process control chemical industry Industrial control Discrete Fourier transforms Fourier transforms Frequency

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Reference system based model predictive control

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IFAC Proceedings Volumes 1996年第1期29卷 5923-5928页

作者： Lokesh Kalra Chriatos Georgakis Chemical Process Modeling and Control Research Center and Department of Chemical Engineering Lehigh University Bethlehem Pennsylvania USA

Despite recent advances in the field, the tuning of presently popular Model Predictive control formulations is largely a trial and error procedure. Motivated by this fact, a Reference System based tuning is explored through Reference System Model Predictive control. The RS-MPC algorithm is examined because of its potentially more intuitive approach to tuning. Under this methodology the tuning involves the selection of two parameters for each controlled variable. The first parameter adjusts the shape of the response and the second one affects the speed. Using these, instead of the weight-based tuning of conventional MPC, much of the trial and error is eliminated. The most important features of the controller arc elucidated through the performance of the STSO and MIMO cases for the Amoco Fluid Catalytic Cracker process simulation.

关键词： Multivariable Feedback control Predictive control Models Tuning Characteristics control Algorithms Simulators

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A Framework for Design of Scheduled Output Feedback Model Predictive control

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IFAC Proceedings Volumes 2004年第1期37卷 71-76页

作者： Zhaoyang Wan Mayuresh V. Kothare Chemical Process Modeling and Control Research Center Department of Chemical Engineering Lehigh University Bethlehem PA 18015

We present a stabilizing scheduled output feedback Model Predictive control (MPC) algorithm for constrained nonlinear systems with large operating regions. We design a set of local output feedback predictive controllers with their estimated regions of stability covering the desired operating region, and implement them as a single scheduled output feedback MPC which on-line switches between the set of local controllers and achieves nonliilear transitions with guaranteed stability. This algorithm provides a general framework for scheduled output feedback MPC design.

关键词： Model predictive control constrained nonlinear systems output feedback scheduling linear matrix inequalities

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Decentralized PCA Charts for Performance Assessment of Plant-Wide control Structures

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IFAC Proceedings Volumes 1996年第1期29卷 5894-5898页

作者： Christos Georgakis Bethany Steadman Vincenzo Liotta Chemical Process Modeling and Control Research Center and Department of Chemical Engineering Lehigh University Bethlehem Pennsylvania USA

Static principal component analysis (PCA) statistical charts are used to assess and compare the performance of two plant-wide control strategies of the Tennessee Eastman process. Both centralized and decentralized charts are used as well as charts relating to the energy and material balance of the process. In most cases these charts reveal the origin of the disturbance and the effectiveness of the control structure to compensate for the disturbance. Differences and similarities between the two control structures are also examined.

关键词： process control large scale systems multivariable feedback systems multivariable quality control control schemes disturbance localization disturbance rejection

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